The files in this repo are arranged in the following way

all data files of type

"tweetX_removedK_mult3_infected.csv"
refer to simulation of tweet # X where the top K most influential users have been blocked by eliminating their ability to produce infection. K will vary between 0-100 for tweet1. 
This file displays which users were infected across all 1000 trials of the simulation

"tweetX_removedK_mult3_infected_by.csv"

is defined the same way, except in contains information on which specific individual infected each other individual

Files of type 

"tweet0_mult3_innoculationKpercent_infected"

refer to simulation of tweet 0 where K% of the dominant infection spreading community for tweet X have been innoculated by reducing
their output infection probabilities by ~20%. K will vary between 0-100 for twee01. This file displays which users were infected across all 1000
trials of the simulation

The below files indicate which users infected other users within the above simulations:
"tweet0_mult3_innoculationKpercent_infected_by" 

The following of files provide information on which community each user belongs to as well as which users follow which
"author_community.csv"
"followers.csv"

all data used to evaluate model in Figure 6 of the manuscript are provided below
(i) "10k_tweets.csv"
(ii) "source_tweets.csv"


all data used needed to produce the ROC_AUC curves produced in the report is in this file
"roc.csv"

the actual post text for all infection seeded in our simulation are provided in txt files. However, we scrub tweet0/tweet1 from this repo since it contains text
of an actual tweet that could be used to identify an individual. The other seeded posts were all synthetically generated.



